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Full-Time

Data ML Engineer

Big Data+Java

Confirmed live in the last 24 hours

LogicMonitor

LogicMonitor

1,001-5,000 employees

Cloud-based IT infrastructure monitoring platform

Data & Analytics
Consulting
Hardware
Enterprise Software
AI & Machine Learning

Senior, Expert

London, UK

Category
Applied Machine Learning
AI Research
AI & Machine Learning
Required Skills
Kubernetes
Apache Spark
Apache Kafka
Docker
Scala
Requirements
  • 6+ years of software development experience in commercial or enterprise applications.
  • 4+ years of full-time Scala development. Writing clean, maintainable and well tested code. With a drive for modern software engineering approaches.
  • In-depth knowledge of scalable data systems, including: NoSQL stores such as HBase; distributed object stores, message queues such as Kafka; distributed filesystems such as S3 and HDFS; data platforms such as Spark.
  • Expertise at building, deploying and tuning jobs with Apache Spark.
  • Ability to write maintainable and deploy well-tested production code.
  • Familiarity with container technology (Docker, Kubernetes, etc.).
  • Experience in working with Data Scientists to turn prototypes in scalable applications.
  • Ability to work with a development team and develop strong, reliable, and effective relationships with team members.
  • Excellent in communication (written and verbal) and collaboration with other functional teams (Support Engineering, Tools, Product, etc.).
  • Degree or higher in computer science or related field.
Responsibilities
  • Prioritise and plan for deliverables in an iterative development strategy.
  • Design, document, code, and test technical solution for new systems or enhancements to existing systems.
  • Working with various teams in LogicMonitor to deliver software products that support LogicMonitor's business growth.
  • Coach and lead other team members from a technical perspective in design and implementation.
  • Envision system features and functionalities by analysing business requirements.
  • Troubleshoot and resolve product/application issues for escalated support cases.
  • Collaborate with a diverse, distributed development organisation. Our development team spans multiple cities in the US, UK and Asia.
  • Ability to tackle performance and design issues at a deep technical level.
  • Understanding and improvement of development process and application deployment.

LogicMonitor operates at the forefront of cloud-based infrastructure monitoring, incorporating AIOps and a suite of automation tools to simplify and optimize IT operations. With an impressive arsenal of over 2,000 integrations, the company facilitates seamless transitions and innovation for businesses of varying scales and complexities. This approach not only positions the company as a leader in IT operations efficiency but also creates a dynamic and resourceful working environment that fosters professional growth and technological advancement.

Company Stage

Series A

Total Funding

$142.9M

Headquarters

Santa Barbara, California

Founded

2007

Growth & Insights
Headcount

6 month growth

-2%

1 year growth

-2%

2 year growth

19%
Simplify Jobs

Simplify's Take

What believers are saying

  • The introduction of AI-driven tools like Edwin AI and LM Co-Pilot can significantly reduce incident response times and alert fatigue, enhancing operational efficiency.
  • The LM Cost Optimization tool can help businesses manage and reduce cloud spending, which is crucial in a down economy, providing a competitive edge.
  • The appointment of experienced leaders like Brooke Cunningham and Karthik Sj can drive strategic growth and innovation, further solidifying LogicMonitor's market position.

What critics are saying

  • The rapid integration of multiple AI tools may lead to complexity and potential usability issues for end-users.
  • The competitive landscape in observability and IT operations is intense, with major players like Splunk and Datadog posing significant threats.

What makes LogicMonitor unique

  • LogicMonitor's integration of generative AI into its observability tools, such as Edwin AI and LM Co-Pilot, sets it apart by offering advanced, interactive experiences for IT operations teams.
  • The LM Cost Optimization tool provides a unique value proposition by combining cost management with hybrid observability, addressing both cloud and on-premises infrastructure.
  • The company's focus on hybrid observability, powered by AI, allows it to cater to complex multi-cloud environments, distinguishing it from competitors who may focus solely on cloud or on-premises solutions.